On the Relationship Between and

Theory, Measurement, and Early Evidence for the Psychological Mechanism

Dissertation Defense

Wednesday, 12 November 2025

Rizqy Amelia Zein

Supervisor: Prof. Dr. Mario Gollwitzer

Chair of Social Psychology, LMU Munich

Theoretical Background

  • Barbour’s Taxonomy (Barbour, 1966, 1998, 2000, 2002) assumes that people can perceive and as:
    • Conflict: inherently incompatible, then cannot mentally coexist.
    • Independence: separate domains or non-overlapping magisteria (Gould, 1999)
    • Dialogue: distinct but incomplete without each other.
    • Integration: a unified belief system with no categorical distinction.
  • Assumptions: The qualitative distinctions between taxons are delicate and they are situation-dependent characteristics (Barbour, 2002).
  • Perceptions of the relationship between and is hereby defined as a mental schema for processing potentially competing explanations and is expected to predict how people interpret, evaluate, and respond to situations in which both scientific and religious explanations are salient.
  • For brevity, I will refer to this construct as ‘mental models’ later on.

Research Questions

Does Barbour’s taxonomy exist in reality? If so, why do people differ in their mental models?

The goal is to illustrate the underlying psychological mechanisms responsible for the formation of the mental models.

Pillar 1: Theory

If it exists, how can one systematically operationalize it for empirical research?

The goal is to quantify qualitative distinctions of the mental models.

Pillar 2: Measure

Then, what does it predict?

The goal is to investigate whether the mental models can predict how people evaluate the utility of specific scientific and religious explanations.

Pillar 3: Mechanistic Testing

Manuscript : Theory

Some Insights

Is the taxonomy real?

  • There is handful of evidence from qualitative studies for Barbour’s taxonomy, mostly in learning sciences, but they are by and large fragmented.
  • Mental models have different names but the most straightforward are suggested by Yasri, Arthur, Smith, & Mancy (2013), which are Conflict, Compartment (= Independence), Complementary (= Dialogue) and Consonance (= Integration).
  • Context-Switch is a new variant (Shipman, Brickhouse, Dagher, & Letts, 2002; Taber, Billingsley, Riga, & Newdick, 2011; Yasri & Mancy, 2012), which represents a pragmatic strategy of an underlying conflict belief by flexibly switching between and depending on the social situation or demands.

Why people differ?

Manuscript : Measurement

Rationale

Rationale

  • We developed a novel measure that mirrors theoretical and empirical descriptions of mental models
  • ..and assumed that people would respond to the scale items by following an unfolding (Thurstone) response process (Carter, Lake, & Zickar, 2010; Roberts, 2018).
  • We performed one pilot and three studies across three (N = 2,920) and one sample (N = 1,197).
  • Since mental models are culturally embedded (C. Johnson, Thigpen, & Funk, 2020; Rios & Aveyard, 2019; Rios & Roth, 2020), the scale might contain systematic cultural bias, so DIF analysis was a necessity.
  • Discriminant, convergent, and criterion-related validity were also examined.

Results

  • Scale data in four samples show that the construct is unidimensional and bipolar.
    • ..but the Context-Switch is closer to compatibility than conflict, unlike previously hypothesized.
  • Generalized Graded Unfolding Model (GGUM) fit better to the data than Generalized Partial Credit Model (GPCM - Likert) in all samples.
  • participants perceive more conflict than at same trait level by ~0.4SD (ETSSD = 0.419).
  • The construct is conceptually distinct from Belief in Science (Farias, Newheiser, Kahane, & de Toledo, 2013) (\(\rho^2\) = .46 , .25 ) and similar to Leicht, Sharp, LaBouff, Zarzeczna, & Elsdon-Baker (2021) scale (\(\rho^2\) = .57 .54 ), but sufficient unshared variance still left.
  • Religiosity, religious identity, and religious upbringing are associated with higher compatibility perceptions in both and samples.

Manuscript : Mechanistic Testing

Rationale & Theory

Goal System Theory (GST)

  • and are means to achieve epistemic goals (i.e., “to explain why things happen”).
  • GST predicts that presenting scientific and religious explanations together (as multiple means) leads to reduced perceived utility of both compared to presenting them alone (i.e., the “dilution effect”, Kruglanski, Pierro, & Sheveland (2011); Bélanger, Schori-Eyal, Pica, Kruglanski, & Lafrenière (2015)).
  • Religious people relied on and moderately, but non-religious people relied on highly (Jackson et al., 2024).
  • Therefore, the number of available (scientific and/or religious) explanations determines how epistemically valuable people perceive these explanations to be.

Motivated Reasoning

  • Prior beliefs play a more important role in determining how epistemically useful people perceive (scientific and/or religious) explanations to be.
  • People engage in biased reasoning, preferring explanations that are consistent with their prior beliefs (Ditto & Lopez, 1992; Kunda, 1990).
  • Moderate reliance on and probably reflects underlying non-conflict beliefs (i.e., compartment, context-switch, complementary, and consonance).
  • High reliance on either or possibly reflects an underlying conflict belief.

Design

  • A within-subject experiment (N = 719)
  • Participants were randomly presented with (scientific or religious), (always one scientific and one religious), and (always two scientific and two religious) of three existential-related incidents (Polt, 1999; Sullivan, Landau, & Kay, 2012): flood, war, and climate crisis.
  • The order of both incidents and number of explanations was counterbalanced using a Latin square design.
  • Then, asked participants to rate each explanation presented to them for their epistemic utility (a 4-item, 7-point Likert scale), their perceptions of the relationship between and , and religiosity.

Results

  • No main effect of n of explanation and no interaction effect between n of explanation and type of explanation.

Results

  • No main effect of n of explanation and no interaction effect between n of explanation and type of explanation.
  • Conflict believers rated religious explanations as less useful than non-conflict believers (d = -0.71). No difference of how scientific explanations was rated between conflict and non-conflict believers (d = 0.001).

Results

  • [No main effect]{mark} of n of explanation and no interaction effect between n of explanation and type of explanation.
  • Conflict believers rated religious explanations as less useful than non-conflict believers (d = -0.71). No difference of how scientific explanations was rated between conflict and non-conflict believers (d = 0.001).
  • Non-religious participants rated religious explanations lower than non-religious did (d = -1.02). No difference in how religious and non-religious participants rated scientific explanations (d = 0.09).

Some Takeaways

Conclusion
  • Manuscript : People’s perceptions on the relationship between and emerge through identifiable cognitive and motivational processes.
  • Manuscript : These perceptions are mapped on to different regions of a unidimensional, bipolar construct, that is culturally embedded.
    • But Context-Switch is closer to compatibility than conflict.
  • Manuscript : This general perception of the relationship between and only predicts how people evaluate the utility of religious explanations, but not scientific explanations.
Contributions
  • Offering a systematic operationalization of Barbour’s taxonomy (Barbour, 1998, 2002).
  • Providing an integrative, but descriptive, psychological mechanism underlying the mental models and early evidence for what they predict.
Limitations
  • No examination of boundary conditions only possible with computational modelling.
  • Only focused on the general perceptions – did not tap into domain/issue/topic-specific perceptions (Leicht et al., 2021).

Thank you! ✨

Where to go from here?

  • Do mental models predict how people change/update their scientific/religious beliefs?
  • Are models stable characteristics or situation-dependent? What are the boundary conditions? (e.g., uncertainty? death-related events? threatened social identity?)
  • Could the models play a role on people’s decision making on various aspects of their life? (e.g., public-health/sustainability-related decision making, etc.)
  • Could science communication strategy be personalized based on one’s preferred model? If so, would it be practically useful?
Project Supported by:

References

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List of Appendices

Manuscript 1

Manuscript 2

Manuscript 2

Manuscript 3

Original Flowchart

Revised Flowchart

Scale Items

Leicht et al (2021)

Correlation Table Study 2 DE

Correlation Table Study 2 USA

Model Fit Pilot + Study 1

Model Fit Study 2

Item Location Study 2

ESSD Study 2

Scale Perceived Utility

Correlation Table

Model Parameter n_exp * type_exp * conflict

Simple Simple Effects n_exp * type_exp * conflict

Model Parameter n_exp * type_exp * religiosity

Simple Simple Effects n_exp * type_exp * religiosity